1. Field of the Invention
The disclosed invention relates to determining the effectiveness of various forms and formats of advertising on the Internet through controlled online experiments.
2. Description of the Background
In traditional commerce, prices are typically static, with change only occurring with major market changes. This has resulted in part because the costs associated with printing fixed-price catalogs, marking goods with prices and advertising prices in the media. Furthermore, it is difficult to offer different prices to different purchasers in a traditional setting in which prices are published or made publicly available.
In addition, advertising campaigns are typically conducted for a substantial period of time before they are updated or changed.
However, e-commerce does not have to be so restricted. The introduction of e-commerce on the Internet has made it easier for Internet merchants to change prices and other market variables by simply updating a Web page or appropriate database/systems. The costs associated with printing catalogs and marking goods in a bricks-and-mortar setting are typically not present in eCommerce. In addition, it is also possible to offer different prices to different customers without either customer learning the price that has been offered to the other. Likewise, it is possible to simultaneous present different advertising campaigns to different Internet customers.
Although it is possible for Internet merchants to update or change advertising and other market variables at any time, typically they have not done so. One reason for sticking to static marketing strategies is that merchants are accustomed to keeping a static advertising campaign. In some cases, merchants have both brick-and-mortar shops and Web shops, and want to keep prices and advertisements in alignment. However, the primary reason why Internet merchants do not dynamically adjust market variables with the ever-changing marketplace is that the merchants do not have the ability to dynamically determine optimal values for the market variables.
In particular, Internet customers may be presented with multiple forms of advertising matter, including graphics, animations, text, audio and video. Such advertising is generally “hot” in the sense that the advertisement itself can be clicked on via a computer mouse or the like, and the user's web browser is redirected to the advertiser's site. Because of this, each such event (or absence thereof) may be tracked and measured. However, very few methods of analyzing any such data exist. Therefore, it is typically not known which forms of advertising or its features, such as color, size, or placement with respect to other matter on a webpage, are most effective in capturing the user's attention. Furthermore, it is possible that such effective may vary with time, culture, socioeconomic status, language, time of day, etc. Additionally, websites undergo frequent updates, and an advertisement that was attention-grabbing on one day may not be so striking after the webpage is updated to a different background color, for example.
The Internet is a dynamic marketplace. As e-commerce becomes a dominant force, the ability to dynamically adjust to and exploit changes in the Internet marketplace becomes critical. An enormous amount of detailed, disaggregate information is being routinely captured during Internet transactions. The ability to gather real-time information on transactions conducted on the Internet means that Internet merchants could use the information to dynamically update their websites to take maximum advantage of market conditions. In particular, real-time transaction information opens up the possibility of dynamic pricing and marketing.
However, using the information to determine the dynamic, optimal market value is problematic. Although a great deal of real-time transactional information is available, businesses have no current method of being able to analyze the information in a manner that provides guidance to dynamically updating pricing, marketing, promotions and other key market variables.
As enterprises move into high velocity environments in a networked economy, decisions based on data are ever more critical and can be leveraged to affect the bottom line. In this environment, information is highly valuable but comes with a high discount rate. That is, the value of the information rapidly depreciates. Current generation data analysis and data mining methods do not effectively deal with this type of information, as current methods rely on a time-consuming sequential process of data gathering, analysis, implementation and feedback.
Current systems including data mining methodologies are retrospective, and there is a significant lag in analysis time. The dynamic nature of the Internet makes even recent information obsolete.
Some efforts have been made to use computer systems to estimate supply and demand, to adjust prices to perceived market conditions, or to vary prices based on the identity and purchasing history of the customer.
U.S. Pat. No. 5,752,238 discloses a consumer-driven electronic information pricing mechanism including a pricing modulator and pricing interface contained with a client system. However, in this reference, the customer selects from a menu of pricing options. It does not disclose or teach a real-time determination of price sensitivities.
U.S. Pat. Nos. 5,822,736 and 5,987,425 disclose a variable margin pricing system and method that generates retail prices based on customer price sensitivity in which products are grouped into pools from a first pool for the most price sensitive products to a last pool for the least price sensitive products. However, the price sensitivities are determined manually by the storekeeper based on his subjective impressions and are not obtained in real-time.
U.S. Pat. No. 5,878,400 discloses a method and apparatus for computing a price to be offered to an organization based on the identity of the organization and the product sought, but does not teach or suggest real-time price determination.
U.S. Pat. No. 5,918,209 discloses a method and system for determining marginal values for perishable resources expiring at a future time, such as an airline seat, hotel room night, or rental car day for use in a perishable resource revenue management system. Data for the perishable resources and composite resources is loaded from the perishable resource revenue management system into the marginal value system. The marginal values for the perishable resources are determined using a continuous optimization function using interdependencies among the perishable resources and the composite resources in the internal data structures. However, this reference does not disclose or teach elicitation of price sensitivities based on measuring customer behavior.
U.S. Pat. No. 5,926,817 discloses a client-server system and method for providing real-time access to a variety of database systems, one application of which is “dynamic price quoting.” However, the reference uses this phrase to mean computing a single price to be quoted to a customer based on information about the user's requirements and data contained in the supplier's databases. It does not teach or suggest experimentation to determine marketplace customer price sensitivity.
In general, the prior art teaches that it is useful to attempt to measure supply and demand as an aid in determining prices. It is also known to utilize previously accumulated facts about a purchaser to influence the price at which a particular product should be offered to him. However, the applicants are not aware of any prior art in which price and other market sensitivities are measured directly through use of controlled real-time experiments.
It is common in the advertising world to conduct surveys to determine the effectiveness of various advertising campaigns. However, because of the speed at which Internet content is generated and modified, it is impractical to conduct human-mediated consumer preference surveys. It might be feasible to do so prior to airing an expensive television commercial, but it is not cost or time effective for webpage advertising.
It is also common for websites to closely monitor “click-through.” Click-through is the number of times users arrive at a site by having clicked on an advertisement. This information is utilized to learn how well an advertisement draws an audience. However, it is not known or suggested in the prior art to measure the effectiveness of advertising by presenting different forms of the same advertisement to selected random samples of the population and measuring relative draw.
In view of the foregoing, it can be appreciated that a substantial need exists for a method and system for dynamically determining the effectiveness of various advertisements.